Papers
A New Approach to Probabilistic Programming Inference
Frank Wood, Jan Willem Meent, Vikash Mansinghka
Accelerating ABC methods using Gaussian processes
Richard Wilkinson
Bayesian Multi-Scale Optimistic Optimization
Ziyu Wang, Babak Shakibi, Lin Jin et al.
Efficient Algorithms and Error Analysis for the Modified Nystrom Method
Shusen Wang, Zhihua Zhang
An LP for Sequential Learning Under Budgets
Joseph Wang, Kirill Trapeznikov, Venkatesh Saligrama
Gaussian Copula Precision Estimation with Missing Values
Huahua Wang, Farideh Fazayeli, Soumyadeep Chatterjee et al.
Linear-time training of nonlinear low-dimensional embeddings
Max Vladymyrov, Miguel Carreira-Perpinan
Active Learning for Undirected Graphical Model Selection
Divyanshu Vats, Robert Nowak, Richard Baraniuk
Path Thresholding: Asymptotically Tuning-Free High-Dimensional Sparse Regression
Divyanshu Vats, Richard Baraniuk
Scaling Graph-based Semi Supervised Learning to Large Number of Labels Using Count-Min Sketch
Partha Talukdar, William Cohen
Adaptive Variable Clustering in Gaussian Graphical Models
Siqi Sun, Yuancheng Zhu, Jinbo Xu
SMERED: A Bayesian Approach to Graphical Record Linkage and De-duplication
Rebecca Steorts, Rob Hall, Stephen Fienberg
Bat Call Identification with Gaussian Process Multinomial Probit Regression and a Dynamic Time Warping Kernel
Vassilios Stathopoulos, Veronica Zamora-Gutierrez, Kate Jones et al.
Explicit Link Between Periodic Covariance Functions and State Space Models
Arno Solin, Simo Särkkä
Loopy Belief Propagation in the Presence of Determinism
David Smith, Vibhav Gogate
In Defense of Minhash over Simhash
Anshumali Shrivastava, Ping Li
Student-t Processes as Alternatives to Gaussian Processes
Amar Shah, Andrew Wilson, Zoubin Ghahramani
Estimating Dependency Structures for non-Gaussian Components with Linear and Energy Correlations
Hiroaki Sasaki, Michael Gutmann, Hayaru Shouno et al.
Lifted MAP Inference for Markov Logic Networks
Somdeb Sarkhel, Deepak Venugopal, Parag Singla et al.
Class Proportion Estimation with Application to Multiclass Anomaly Rejection
Tyler Sanderson, Clayton Scott
Learning Structured Models with the AUC Loss and Its Generalizations
Nir Rosenfeld, Ofer Meshi, Danny Tarlow et al.
Sequential crowdsourced labeling as an epsilon-greedy exploration in a Markov Decision Process
Vikas Raykar, Priyanka Agrawal
Cluster Canonical Correlation Analysis
Nikhil Rasiwasia, Dhruv Mahajan, Vijay Mahadevan et al.
Black Box Variational Inference
Rajesh Ranganath, Sean Gerrish, David Blei
An Analysis of Active Learning with Uniform Feature Noise
Aaditya Ramdas, Barnabas Poczos, Aarti Singh et al.